Python 打印热图打印未渲染所有yaxis标签

我用热图设计了一个仪表盘。但是，我注意到t=y轴上的一些标签没有显示。我只得到了有限的钱，我不知道出了什么问题。这是我的仪表板：

import dash
import dash_table
import plotly.graph_objs as go
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input,Output
import pandas as pd
import os
import numpy as np
#correlation dataframe
correlation_df = supervisor[['Características (D)', 'Características (I)',
       'Características (S)', 'Características (C)', 'Motivación (D)',
       'Motivación (I)', 'Motivación (S)', 'Motivación (C)', 'Bajo Stress (D)',
       'Bajo Stress (I)', 'Bajo Stress (S)', 'Bajo Stress (C)','span','Mean Team Performance','employment span','Pay to team size ratio']]
correlation_df  = correlation_df.corr()
corr_fig = go.Figure()
corr_fig.add_trace(go.Heatmap(
    z= correlation_df.values,
    x= ['Características (D)', 'Características (I)',
       'Características (S)', 'Características (C)', 'Motivación (D)',
       'Motivación (I)', 'Motivación (S)', 'Motivación (C)', 'Bajo Stress (D)',
       'Bajo Stress (I)', 'Bajo Stress (S)', 'Bajo Stress (C)','span','Mean Team Performance','employment span','Pay to team size ratio'],
    y= ['Características (D)', 'Características (I)',
       'Características (S)', 'Características (C)', 'Motivación (D)',
       'Motivación (I)', 'Motivación (S)', 'Motivación (C)', 'Bajo Stress (D)',
       'Bajo Stress (I)', 'Bajo Stress (S)', 'Bajo Stress (C)','span','Mean Team Performance','employment span','Pay to team size ratio'],
    hoverongaps=False
))
corr_fig.update_layout(title="Correlation heatmap",
                  yaxis={"title": 'Traits'},
                  xaxis={"title": 'Traits',"tickangle": 45}, )
app = dash.Dash()
#html layout
app.layout = html.Div(children=[
    html.H1(children='Dashboard', style={
        'textAlign': 'center',
        'height': '10'
    }),
    dcc.Graph(
        id='heatmap',
        figure=corr_fig.to_dict()
    )
    ])
if __name__ == '__main__':
        app.run_server(debug=True)

以下是我的数据帧示例：

{'Características (D)': {'Características (D)': 1.0,
  'Características (I)': -0.744432853713455,
  'Características (S)': 0.20085563028990697,
  'Características (C)': -0.039907357919985106,
  'Motivación (D)': 0.8232188768568326,
  'Motivación (I)': -0.6987940156295481,
  'Motivación (S)': 0.17336394623619988,
  'Motivación (C)': -0.03941838984936696,
  'Bajo Stress (D)': 0.8142337605566142,
  'Bajo Stress (I)': -0.48861318810993065,
  'Bajo Stress (S)': 0.3207614659369065,
  'Bajo Stress (C)': -0.0461134826855843,
  'span': 0.2874881163983965,
  'Mean Team Performance': 0.40633858242603244,
  'employment span': -0.09857697245687172,
  'Pay to team size ratio': 0.022958588188126107},
 'Características (I)': {'Características (D)': -0.744432853713455,
  'Características (I)': 1.0,
  'Características (S)': -0.3779100652350093,
  'Características (C)': -0.11879176229148546,
  'Motivación (D)': -0.8454566900924195,
  'Motivación (I)': 0.8314885901746485,
  'Motivación (S)': -0.5493813305976118,
  'Motivación (C)': 0.020902885445784,
  'Bajo Stress (D)': -0.4614762821424876,
  'Bajo Stress (I)': 0.8628000011272827,
  'Bajo Stress (S)': 0.07723803992022794,
  'Bajo Stress (C)': -0.26492408476089707,
  'span': -0.2923189384010105,
  'Mean Team Performance': -0.04150083345671622,
  'employment span': 0.4006484556146567,
  'Pay to team size ratio': 0.27081339758378836},
 'Características (S)': {'Características (D)': 0.20085563028990697,
  'Características (I)': -0.3779100652350093,
  'Características (S)': 1.0,
  'Características (C)': -0.7739057580439489,
  'Motivación (D)': 0.28928161764191546,
  'Motivación (I)': -0.14811042351159115,
  'Motivación (S)': 0.7823864767779756,
  'Motivación (C)': -0.6651182815949327,
  'Bajo Stress (D)': 0.10162624205618695,
  'Bajo Stress (I)': -0.5488737066087104,
  'Bajo Stress (S)': 0.46905181352171205,
  'Bajo Stress (C)': -0.4698328671560004,
  'span': -0.02087671997992093,
  'Mean Team Performance': -0.12496266913575294,
  'employment span': 0.27001694775950746,
  'Pay to team size ratio': 0.07931062556531454},
 'Características (C)': {'Características (D)': -0.039907357919985106,
  'Características (I)': -0.11879176229148546,
  'Características (S)': -0.7739057580439489,
  'Características (C)': 1.0,
  'Motivación (D)': -0.011616389427962759,
  'Motivación (I)': -0.292733356844308,
  'Motivación (S)': -0.4343733032773228,
  'Motivación (C)': 0.774357808826908,
  'Bajo Stress (D)': -0.04367706074639601,
  'Bajo Stress (I)': 0.0931714388059811,
  'Bajo Stress (S)': -0.6482541912883304,
  'Bajo Stress (C)': 0.7732581689662739,
  'span': 0.03775247426826095,
  'Mean Team Performance': -0.07825282894287325,
  'employment span': -0.5003613024138532,
  'Pay to team size ratio': -0.20937248430293648},
 'Motivación (D)': {'Características (D)': 0.8232188768568326,
  'Características (I)': -0.8454566900924195,
  'Características (S)': 0.28928161764191546,
  'Características (C)': -0.011616389427962759,
  'Motivación (D)': 1.0,
  'Motivación (I)': -0.6401977926528387,
  'Motivación (S)': 0.27806883694592277,
  'Motivación (C)': -0.2534345146499511,
  'Bajo Stress (D)': 0.35748019323906,
  'Bajo Stress (I)': -0.7219032007713697,
  'Bajo Stress (S)': 0.21293087519106632,
  'Bajo Stress (C)': 0.2698254124168881,
  'span': 0.5037240436882805,
  'Mean Team Performance': 0.48414442720369955,
  'employment span': -0.20711331594020507,
  'Pay to team size ratio': -0.3769998767635495},
 'Motivación (I)': {'Características (D)': -0.6987940156295481,
  'Características (I)': 0.8314885901746485,
  'Características (S)': -0.14811042351159115,
  'Características (C)': -0.292733356844308,
  'Motivación (D)': -0.6401977926528387,
  'Motivación (I)': 1.0,
  'Motivación (S)': -0.48288361435623983,
  'Motivación (C)': -0.4135335004412625,
  'Bajo Stress (D)': -0.5563645790627242,
  'Bajo Stress (I)': 0.45272622386580263,
  'Bajo Stress (S)': 0.31345796324782077,
  'Bajo Stress (C)': -0.1236088717264958,
  'span': -0.4334332491868192,
  'Mean Team Performance': -0.027223644357210867,
  'employment span': 0.08277408562811393,
  'Pay to team size ratio': 0.30770777808996924},
 'Motivación (S)': {'Características (D)': 0.17336394623619988,
  'Características (I)': -0.5493813305976118,
  'Características (S)': 0.7823864767779756,
  'Características (C)': -0.4343733032773228,
  'Motivación (D)': 0.27806883694592277,
  'Motivación (I)': -0.48288361435623983,
  'Motivación (S)': 1.0,
  'Motivación (C)': -0.23220036735524985,
  'Bajo Stress (D)': 0.12079023858043715,
  'Bajo Stress (I)': -0.5418626995091027,
  'Bajo Stress (S)': -0.12381340765657087,
  'Bajo Stress (C)': -0.3091698232697242,
  'span': 0.1503231802207429,
  'Mean Team Performance': -0.38838798587565976,
  'employment span': 0.09981399691805137,
  'Pay to team size ratio': -0.20858825983296703},
 'Motivación (C)': {'Características (D)': -0.03941838984936696,
  'Características (I)': 0.020902885445784,
  'Características (S)': -0.6651182815949327,
  'Características (C)': 0.774357808826908,
  'Motivación (D)': -0.2534345146499511,
  'Motivación (I)': -0.4135335004412625,
  'Motivación (S)': -0.23220036735524985,
  'Motivación (C)': 1.0,
  'Bajo Stress (D)': 0.18028688548066718,
  'Bajo Stress (I)': 0.386437402512207,
  'Bajo Stress (S)': -0.7351725371592022,
  'Bajo Stress (C)': 0.21452556505271267,
  'span': 0.15796613914842977,
  'Mean Team Performance': -0.11411844367303944,
  'employment span': -0.1335403092401566,
  'Pay to team size ratio': -0.16110863218572585},
 'Bajo Stress (D)': {'Características (D)': 0.8142337605566142,
  'Características (I)': -0.4614762821424876,
  'Características (S)': 0.10162624205618695,
  'Características (C)': -0.04367706074639601,
  'Motivación (D)': 0.35748019323906,
  'Motivación (I)': -0.5563645790627242,
  'Motivación (S)': 0.12079023858043715,
  'Motivación (C)': 0.18028688548066718,
  'Bajo Stress (D)': 1.0,
  'Bajo Stress (I)': -0.1849352428080063,
  'Bajo Stress (S)': 0.2529157606770202,
  'Bajo Stress (C)': -0.31055770095686547,
  'span': -0.11631187918782246,
  'Mean Team Performance': 0.05369401779765192,
  'employment span': -0.042901905999867325,
  'Pay to team size ratio': 0.4484652828139771},
 'Bajo Stress (I)': {'Características (D)': -0.48861318810993065,
  'Características (I)': 0.8628000011272827,
  'Características (S)': -0.5488737066087104,
  'Características (C)': 0.0931714388059811,
  'Motivación (D)': -0.7219032007713697,
  'Motivación (I)': 0.45272622386580263,
  'Motivación (S)': -0.5418626995091027,
  'Motivación (C)': 0.386437402512207,
  'Bajo Stress (D)': -0.1849352428080063,
  'Bajo Stress (I)': 1.0,
  'Bajo Stress (S)': -0.0981237735359993,
  'Bajo Stress (C)': -0.27961420029017486,
  'span': -0.06711566955045667,
  'Mean Team Performance': 0.06327392392569486,
  'employment span': 0.5471491483201977,
  'Pay to team size ratio': 0.17612214868518486},
 'Bajo Stress (S)': {'Características (D)': 0.3207614659369065,
  'Características (I)': 0.07723803992022794,
  'Características (S)': 0.46905181352171205,
  'Características (C)': -0.6482541912883304,
  'Motivación (D)': 0.21293087519106632,
  'Motivación (I)': 0.31345796324782077,
  'Motivación (S)': -0.12381340765657087,
  'Motivación (C)': -0.7351725371592022,
  'Bajo Stress (D)': 0.2529157606770202,
  'Bajo Stress (I)': -0.0981237735359993,
  'Bajo Stress (S)': 1.0,
  'Bajo Stress (C)': -0.3570697743190169,
  'span': -0.23885238917830093,
  'Mean Team Performance': 0.41404235485716345,
  'employment span': 0.33146618322475935,
  'Pay to team size ratio': 0.49978958145813196},
 'Bajo Stress (C)': {'Características (D)': -0.0461134826855843,
  'Características (I)': -0.26492408476089707,
  'Características (S)': -0.4698328671560004,
  'Características (C)': 0.7732581689662739,
  'Motivación (D)': 0.2698254124168881,
  'Motivación (I)': -0.1236088717264958,
  'Motivación (S)': -0.3091698232697242,
  'Motivación (C)': 0.21452556505271267,
  'Bajo Stress (D)': -0.31055770095686547,
  'Bajo Stress (I)': -0.27961420029017486,
  'Bajo Stress (S)': -0.3570697743190169,
  'Bajo Stress (C)': 1.0,
  'span': -0.01344626398272969,
  'Mean Team Performance': -0.08070306908833835,
  'employment span': -0.5968535698213163,
  'Pay to team size ratio': -0.2795657757692292},
 'span': {'Características (D)': 0.2874881163983965,
  'Características (I)': -0.2923189384010105,
  'Características (S)': -0.02087671997992093,
  'Características (C)': 0.03775247426826095,
  'Motivación (D)': 0.5037240436882805,
  'Motivación (I)': -0.4334332491868192,
  'Motivación (S)': 0.1503231802207429,
  'Motivación (C)': 0.15796613914842977,
  'Bajo Stress (D)': -0.11631187918782246,
  'Bajo Stress (I)': -0.06711566955045667,
  'Bajo Stress (S)': -0.23885238917830093,
  'Bajo Stress (C)': -0.01344626398272969,
  'span': 1.0,
  'Mean Team Performance': -0.19851531030268585,
  'employment span': 0.13994502995917002,
  'Pay to team size ratio': -0.802380461421258},
 'Mean Team Performance': {'Características (D)': 0.40633858242603244,
  'Características (I)': -0.04150083345671622,
  'Características (S)': -0.12496266913575294,
  'Características (C)': -0.07825282894287325,
  'Motivación (D)': 0.48414442720369955,
  'Motivación (I)': -0.027223644357210867,
  'Motivación (S)': -0.38838798587565976,
  'Motivación (C)': -0.11411844367303944,
  'Bajo Stress (D)': 0.05369401779765192,
  'Bajo Stress (I)': 0.06327392392569486,
  'Bajo Stress (S)': 0.41404235485716345,
  'Bajo Stress (C)': -0.08070306908833835,
  'span': -0.19851531030268585,
  'Mean Team Performance': 1.0,
  'employment span': 0.3992240651662481,
  'Pay to team size ratio': 0.38910257451919805},
 'employment span': {'Características (D)': -0.09857697245687172,
  'Características (I)': 0.4006484556146567,
  'Características (S)': 0.27001694775950746,
  'Características (C)': -0.5003613024138532,
  'Motivación (D)': -0.20711331594020507,
  'Motivación (I)': 0.08277408562811393,
  'Motivación (S)': 0.09981399691805137,
  'Motivación (C)': -0.1335403092401566,
  'Bajo Stress (D)': -0.042901905999867325,
  'Bajo Stress (I)': 0.5471491483201977,
  'Bajo Stress (S)': 0.33146618322475935,
  'Bajo Stress (C)': -0.5968535698213163,
  'span': 0.13994502995917002,
  'Mean Team Performance': 0.3992240651662481,
  'employment span': 1.0,
  'Pay to team size ratio': 0.04572394154746432},
 'Pay to team size ratio': {'Características (D)': 0.022958588188126107,
  'Características (I)': 0.27081339758378836,
  'Características (S)': 0.07931062556531454,
  'Características (C)': -0.20937248430293648,
  'Motivación (D)': -0.3769998767635495,
  'Motivación (I)': 0.30770777808996924,
  'Motivación (S)': -0.20858825983296703,
  'Motivación (C)': -0.16110863218572585,
  'Bajo Stress (D)': 0.4484652828139771,
  'Bajo Stress (I)': 0.17612214868518486,
  'Bajo Stress (S)': 0.49978958145813196,
  'Bajo Stress (C)': -0.2795657757692292,
  'span': -0.802380461421258,
  'Mean Team Performance': 0.38910257451919805,
  'employment span': 0.04572394154746432,
  'Pay to team size ratio': 1.0}}

这是运行我的代码时热图的快照：

---

所以我可以通过增加热图的长度来解决这个问题。我假设由于我的热图的大小，一些y标签被剪掉了

corr_fig.update_layout(title="Correlation heatmap",
                  yaxis={"title": 'Traits'},
                  width=1200,
                  height=1400,
                  xaxis={"title": 'Traits',"tickangle": 45}, )

---

您可以使用布局的

yaxis\u nticks

属性指定要显示的记号数

例如，数据框中的行数可以与刻度数相同

corr\u图更新布局（title=“相关热图”，
yaxis={“title”：“Traits”}，
xaxis={“title”：“Traits”，“tickagle”：45}，
yaxis_nticks=len（主管））

它呈现为

---

你可以缩小你的例子，因为这里不需要破折号。实际上，奇怪的是，绘图是在固定比例上生成的，与y标签无关